Triple
T20009287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotswold vernacular architecture |
E494544
|
entity |
| Predicate | characteristicMaterial |
P104293
|
FINISHED |
| Object | Cotswold limestone |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cotswold limestone | Statement: [Cotswold vernacular architecture, characteristicMaterial, Cotswold limestone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicMaterial Context triple: [Cotswold vernacular architecture, characteristicMaterial, Cotswold limestone]
-
A.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
featuresMaterialType
chosen
Indicates that an entity is characterized by or incorporates a specific type of material.
-
C.
exteriorMaterial
Indicates the material that forms the outer surface or outer construction of an object or structure.
-
D.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
E.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a81c5881909692fcaaf59a57c9 |
completed | April 20, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:33 p.m.